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MSc Machine Learning and Data Science (Online)

Imperial College London

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Course options

  • Qualification

    MSc - Master of Science

  • Location

    Online

  • Study mode

    Distance / Online

  • Start date

    SEP

  • Duration

    2 Years

Course summary

Accelerate your career in industry or research with this online, part-time master’s course, integrating mathematical rigor with practical machine learning and data science skills.

You’ll gain expertise in tackling complex data by implementing scalable solutions using industry-standard tools, including PySpark. You’ll enhance your analytical abilities in mathematics and statistics and also explore the limitations of machine learning methods and learn how to ethically apply these techniques to your work.

This course covers a diverse range of topics in theoretical and applied perspectives, focusing on statistical estimation, prediction and anomaly detection. Topics also include fundamentals of probability and decision theory, advanced deep learning, reinforcement learning techniques, supervised and unsupervised learning, Bayesian methods and unstructured data processing.

Finally, you will have the opportunity to apply the knowledge you have gained from the taught programme through an extensive research project, carried out in collaboration with a member of academic staff.

All learning is delivered online.

Tuition fees

Students living in United States
(International fees)

£ 17,850per year

Tuition fees shown are for indicative purposes and may vary. Please check with the institution for most up to date details.

University information

Imperial College London

  • University League Table

    6th

  • Campus address

    South Kensington Campus, Exhibition Rd, London, Greater London, SW7 2AZ, United Kingdom

Subject rankings

  • Subject ranking

    3rd out of 117

  • Entry standards

    / Max 223
    217 97%

    5th

  • Graduate prospects

    / Max 100
    97.0 97%

    4th

    1
  • Student satisfaction

    / Max 4
    3.13 78%

    29th

    13

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